@article{98208,
  keywords = {General Medicine, Leprosy, Health information systems, Public Health Surveillance, Epidemiology, Descriptive, Epidemiological Monitoring},
  author = {Mendes MDS and Oliveira ALSD and Schindler HC},
  title = {Evaluation of completeness, consistency and non-duplication of leprosy notification data on the Notifiable Health Conditions Information System, João Pessoa, Paraíba, Brazil: a descriptive study, 2001-2019},
  abstract = {<p><strong>Objective:</strong> to analyze the completeness, consistency and non-duplication of leprosy notification data in João Pessoa, Paraíba, Brazil, 2001-2019.</p>

<p><strong>Methods:</strong>&nbsp;this was a descriptive study, conducted with data from the Notifiable Health Conditions Information System, which checked for “duplication” (acceptable: &lt; 5%), “completeness” (excellent = incompleteness ≤ 5%) and “consistency” (excellent: ≥ 90.0%), based on the proportion of complete and consistent fields.</p>

<p><strong>Results:</strong> the sample consisted of 2,410 notifications. Duplication was acceptable (0.3%). The completeness of the “bacilloscopy”, “affected nerves”, “examined contacts” and “reactive episode” fields was very poor (more than 50% incomplete). Consistency between the “operational classification” and “initial treatment regimen” fields was excellent (99.6%), while consistency between “operational classification” and “clinical form” was low (50.7%).</p>

<p><strong>Conclusion:</strong> although duplication was acceptable, poor completeness of diagnosis and follow-up fields hinders epidemiological analysis, recognition of the status of the disease and adoption of measures to control it.</p>
},
  year = {2023},
  journal = {Epidemiologia e Serviços de Saúde},
  volume = {32},
  publisher = {FapUNIFESP (SciELO)},
  issn = {2237-9622, 1679-4974},
  url = {https://www.scielosp.org/pdf/ress/2023.v32n2/e2022734/en},
  doi = {10.1590/s2237-96222023000200008},
}